Simulating urban expansion and scenario prediction using a cellular automata urban growth model, SLEUTH, through a case study of Karaj City, Iran

Abstract

Understanding, analysis, monitoring and modeling of urban growth evolution as a major driving force of land use/land cover transformation, especially in developing countries, is of great importance for land managers in the process of sustainable development. Using spatial predictive models and change detection techniques can provide an additional level of knowledge of the causes and impacts of urban growth mechanisms, which finally provide comprehensive insight into urban chronology. Karaj, the capital of Alborz province, has been experiencing a substantial increase in total area of urban environments mainly due to its socioeconomic attractions during the last three decades. The present work aims to reveal how the historical trend of the urban growth can affect its future spatial pattern. For conducting this study, the SLEUTH cellular automata urban growth model was executed via three calibration steps including coarse, fine and final. Relying on the calibrated model, dynamics of the Karaj City were predicted under its historical trend as well as two different scenarios including compact and extensive growth up to year 2040. According to the findings of the present study, while extensive growth option indicates the most consumption of the vacant lands, the compact scenario dictates infill form of the urban growth in addition to saving spaces. Finally, urban growth forecasting based on its historical trend illustrates that total area of the human-constructed elements will be in the middle of other two predictive scenarios.